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Creators/Authors contains: "Hung, Shao-Tse"

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  1. ; ; ; ; ; (, ACM IMC 2024)
    Free, publicly-accessible full text available November 4, 2025
  2. ; ; ; ; ; (, ACM)
    While sketch-based network telemetry is attractive, realizing its potential benefits has been elusive in practice. Existing sketch so- lutions offer low-level interfaces and impose high effort on op- erators to satisfy telemetry intents with required accuracies. Ex- tending these approaches to reduce effort results in inefficient deployments with poor accuracy-resource tradeoffs. We present SketchPlan, an abstraction layer for sketch-based telemetry to re- duce effort and achieve high efficiency. SketchPlan takes an en- semble view across telemetry intents and sketches, instead of ex- isting approaches that consider each intent-sketch pair in isola- tion. We show that SketchPlan improves accuracy-resource trade- offs by up-to 12x and up-to 60x vs. baselines, in single-node and network-wide settings. SketchPlan is open-sourced at: https: //github.com/milindsrivastava1997/SketchPlan 
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    Free, publicly-accessible full text available November 4, 2025
  3. ; ; ; ; ; (, ACM IMC)
    While sketch-based network telemetry is attractive, realizing its potential benefits has been elusive in practice. Existing sketch solutions offer low-level interfaces and impose high effort on operators to satisfy telemetry intents with required accuracies. Extending these approaches to reduce effort results in inefficient deployments with poor accuracy-resource tradeoffs. We present SketchPlan, an abstraction layer for sketch-based telemetry to reduce effort and achieve high efficiency. SketchPlan’s takes an ensemble view across telemetry intents and sketches, instead of existing approaches that consider each intent-sketch pair in isolation. We show that SketchPlan improves accuracy-resource tradeoffs by up-to 12x and up-to 60x vs. baselines, in single-node and network-wide settings. 
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    Accepted Manuscript Full Text Available